It is impossible for any business to remain untouched by the possibility of losing customers. The challenge, however, is to ensure that a single instance does not lead to the loss of several customers. The consequences of such events not only affect the brand financially but also diminishes its position and competitiveness in the market.

Customer acquisition and retention are fundamental focus areas for any brand looking to build stronger, longer, and more fruitful relationships with their consumers today. Apart from in-depth strategizing, brands are required to effectively engage their customers and provide them with a distinctive experience during all interactions, across all channels. Doing so can ultimately influence whether or not a consumer becomes a loyal customer.

The Importance of Building Strong Customer Relationships

This holds particularly true in the present business ecosystem, where consumers have an abundance of choices and information. With the target audiences having the upper hand, customer retention becomes a substantial challenge for businesses in any industry. Conventional cookie-cutter methods of acquiring and retaining customers just do not work today.

However, most brands tend to overlook this change in market dynamics. This can be a costly oversight. Various industry studies highlight how acquiring new customers can cost five times more than it does to retain existing ones. This should be a reason big enough for brands to emphasize on customer engagement and relationship building.

Capitalizing on Artificial Intelligence and Automation to Drive on Enhanced Customer Experiences

In recent times, Artificial Intelligence has emerged as a powerful tool for brands and marketers. By leveraging advanced business intelligence, AI-driven automated tools can turn data from multiple, disparate sources into valuable insights. More interestingly, the more data is fed into the system, the more accurate these insights become – and the higher is the business value driven.

Moreover, by integrating an AI-based solution with the organization’s customer relationship and data management interfaces, marketers can ensure more accurate end-user assessments and deploy the right strategic interventions. Such integrations can also offer the following benefits:

Predicting churn

Machine learning algorithms can be programmed to collect data on at-risk customers. Artificial intelligence-powered tools can accordingly augment customer engagement efforts. Such interventions can help brands define the ‘how’, ‘what’, and ‘where’ to create the maximum impact. This is true for specific time-based campaigns, as well as for a brand’s routine market communications.

A study by Forrester showed that AI-based customer management solutions can lower customer churn by 10-50%. Their computation power can assess vast amounts of customer data to predict the likelihood of a customer discontinuing his/her relationship with a brand. AI not only helps in swiftly cleaning large amounts of raw data but also extensively analyzing these data sets to develop predictive models for identifying customers who might pose the threat of churning. Brands can then create the right strategies and implement them at the right time and place, as well as identify the signs that indicate a customer’s dissatisfaction with the brand during any stage of their lifecycle.

Personalizing content

Machine learning and predictive modeling tools can also be leveraged to determine how customers respond to brand communications across channels. This information can then be applied to achieve the desired outcomes from marketing campaigns, sales promotions, incentives, etc. Data-driven insights can help brands to create personalized, targeted communications in the form of e-mail/SMS content, social media ads, or posts which are aligned with a customer’s historical data and purchase behavior. Adding context and customization to messaging can maximize the impact of campaigns and significantly bring down the cost of selling to each customer.

Social analytics to understand customers

The increase in the number of customers active on social has created the need of AI-driven social media analytics. Social AI can provide enterprises with better insights by analyzing the data available on customers’ social media/digital activities, interactions, buying patterns, etc. It can also help brands monitor and analyze forms of communication, along with equipping marketers with the data and insights to help them strategize and customize marketing communications, activities, etc.

Offer customers real-time recommendations

An extension of the personalization capabilities of AI, data analytics and predictive intelligence tools study customer data such as their past purchases, consumption patterns, preferences, intent, etc. These details help marketers predict selling opportunities and time their reach outs to maximize the impact on purchase decisions. AI-powered tools can be programmed to generate product recommendations, discounts, and call-to-action messages. These messages can be customized to match each customer’s profile based on successful interactions in the past.

Enabling smart customer interactions

AI-driven customer service tools allow brands to understand their target audiences better, especially when the interactions between the two are studied in detail using data and analytics. The combination of Artificial Intelligence, analytics, and Machine Learning can deliver insights that can be leveraged to create highly personalized solutions and query resolutions for each customer. Applying these insights proactively across each stage of the customer lifecycle allows brands to engage and retain customers more efficiently. Such a personalized approach to customer service has the potential to delight customers and eventually turn them into loyal customers.

Today, adopting AI-driven solutions across various departments like sales, marketing, and customer relationship management is crucial for brands to ensure effective, proactive engagement with their consumers. AI-driven technologies using multiple data sources enable marketers to map each stage of the customer journey and initiate meaningful engagement opportunities with them. It allows businesses to identify existing gaps in the customer experience, extract relevant insights, and take the necessary efforts to retain customers, keep them engaged, and increase their delight with each interaction with the brand.